Healthcare Workers’ Awareness Level on Biometric Controlled Health Informatics: A Case of Uganda Public Hospitals

Nicholars, Jude Iyke (2025) Healthcare Workers’ Awareness Level on Biometric Controlled Health Informatics: A Case of Uganda Public Hospitals. International Journal of Innovative Science and Research Technology, 10 (10): 25oct1093. pp. 1421-1427. ISSN 2456-2165

Abstract

The successful implementation of Biometric Controlled Health Informatics is based upon end-user awareness and acceptance (World Health Organization, 2021). In Uganda, the national e-health strategy advocated for the adoption of Biometric Controlled Health Informatics to enhance hospital service delivery and data security (Ministry of Health, 2016). However, the integration of Biometric Controlled Health Informatics, a system designed to securely manage patient records and health workers' data, remains limited. Establishing the level of health workers' awareness is a critical step, as a lack of awareness and understanding can lead to resistance, improper use, and ultimately, the failure of such technological interventions (Nigam et al., 2022 & Venkatesh & Bala, 2008This study established awareness of Biometric Controlled Health Informatics among clinical and non-clinical health workers at Gulu and Soroti Regional Referral Hospitals, offering valuable insights to guide tailored implementation strategies for this innovative technology in Uganda's health system. Using a mixed methods approach that combined qualitative and quantitative techniques within one study (Creswell & Plano Clark, 2023), the research provided a comprehensive understanding of the issue. The quantitative phase examined the relationship between health workers’ personality traits (independent variables) and their acceptance of biometric-controlled health informatics (dependent variable) through standardized tools: the Big Five Inventory (BFI) and a Technology Acceptance Model (TAM) questionnaire. This enabled statistical analysis using correlation and multiple regression to measure the strength and direction of these relationships (Pallant, 2020). The sample included 244 health workers from Gulu (52.0%) and Soroti (48.0%) hospitals, with this balanced representation reducing potential institutional bias. Quantitative results showed that around 57% of participants had prior knowledge of biometric authentication systems, and about 56.6% had used biometric data—primarily fingerprint scanning for attendance monitoring. Qualitative findings revealed that while most non-technical staff recognized biometrics mainly as attendance tools, technical staff were more aware of their broader use in securing patient records. However, there was limited understanding of biometric applications beyond attendance, highlighting a need for enhanced training and awareness programs. Challenges such as technical glitches and perceptions of biometrics as controlling rather than enabling technology influenced levels of awareness and acceptance among health workers.

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